Results 51 to 60 of about 14,911 (257)

Heavy Tailed Distribution of Binary Classification Model

open access: yesJournal of Sciences, Islamic Republic of Iran, 2023
The proposed research incorporates the utilization of a heavy-tailed skewed distribution referred to as the inverse Weibull as a link function in the context of a binary classification model. This selection is motivated by the need to address the existence of rare or extreme events in random processes.
Oladimeji, Damilare   +2 more
openaire   +2 more sources

CSF Monoamine Metabolites and Cognitive Trajectory in Early Parkinson's Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Imaging and postmortem studies indicate that abnormalities in monoaminergic neurotransmission contribute to cognitive impairment in Parkinson's disease (PD). However, it remains uncertain if cerebrospinal fluid (CSF) monoamine metabolites can serve as biomarkers of cognitive decline in early PD.
Jing‐Yu Shao   +7 more
wiley   +1 more source

Estimating 𝐿-Functionals for Heavy-Tailed Distributions and Application

open access: yesJournal of Probability and Statistics, 2010
𝐿-functionals summarize numerous statistical parameters and actuarial risk measures. Their sample estimators are linear combinations of order statistics (𝐿-statistics). There exists a class of heavy-tailed distributions for which the asymptotic normality
Abdelhakim Necir, Djamel Meraghni
doaj   +1 more source

The Arcsine Exponentiated-X Family: Validation and Insurance Application

open access: yesComplexity, 2020
In this paper, we propose a family of heavy tailed distributions, by incorporating a trigonometric function called the arcsine exponentiated-X family of distributions.
Wenjing He   +3 more
doaj   +1 more source

On the interference arising from random spatial fields of interferers utilizing multiple subcarriers

open access: yesEURASIP Journal on Wireless Communications and Networking, 2022
Effective symbol detection, channel estimation and decoding of channel codes require an accurate characterization of the noise probability distribution.
Ce Zheng   +4 more
doaj   +1 more source

Private Mean Estimation of Heavy-Tailed Distributions

open access: yesCoRR, 2020
Appeared in COLT ...
Gautam Kamath 0001   +2 more
openaire   +3 more sources

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

open access: yesAdvanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch   +3 more
wiley   +1 more source

High‐Temperature Phase Transformation in a V‐9Si‐6.5B Alloy: The Kinetic and Crystallographic Pathway From V5SiB2 to V8SiB4

open access: yesAdvanced Engineering Materials, EarlyView.
In situ synchrotron high‐energy X‐ray diffraction reveals the real‐time high‐temperature phase evolution of a ternary V‐9Si‐6.5B alloy. The study uncovers a kinetically delayed V5SiB2 → V8SiB4 transformation governed by massive structural and chemical barriers.
Zahra Sabeti   +4 more
wiley   +1 more source

Time Scale Transformation in Bivariate Pearson Diffusions: A Shift from Light to Heavy Tails

open access: yesAxioms
Heavy-tailed Pearson diffusions provide a natural alternative to well-known Ornstein–Uhlenbeck and Cox–Ingersoll–Ross processes in applications that require addressing heavy-tailed behavior.
Nenad Šuvak
doaj   +1 more source

Heavy-tailed distributions in combinatorial search

open access: yes, 1997
Combinatorial search methods often exhibit a large variability in performance. We study the cost profiles of combinatorial search procedures. Our study reveals some intriguing properties of such cost profiles. The distributions are often characterized by very long tails or "heavy tails". We will show that these distributions are best characterized by a
Gomes, Carla P.   +2 more
openaire   +2 more sources

Home - About - Disclaimer - Privacy